> My github gist proves that all of these techniques found in automatic1111 work with NLP models No it doesn't, your gist just shows that it's possible to impl

> My github gist proves that all of these techniques found in automatic1111 work with NLP models No it doesn't, your gist just shows that it's possible to implement, which I'm not disputing. And even then, your example with GPT-2 has the comment "GPT2 is very tempermental with this technique" and requires a temperature of 20 to behave which is an accommodation that can never be used in a real application. If you can create test cases and demos where prompt weighting in a LLM results in a distinct observable improvement as it does with diffusion models, that would be a different story. I'd love to be proven wrong but your gist doesn't do it.